Copyright © 2016-2018

Copies of this document may be made for your own use and for distribution to others, provided that you do not charge any fee for such copies and further provided that each copy contains this Copyright Notice, whether distributed in print or electronically.

1. Introduction

The Holon JDBC Datastore is the Java DataBase Connectivity reference implementation of the Datastore API.

See the Datastore documentation for further information about the Datastore API.

The JDBC Datastore implementation uses the Java javax.sql.DataSource API to access the the physical data source and the SQL language to perform data access and management operations.

1.1. Sources and contributions

The Holon Platform JDBC Datastore module source code is available from the GitHub repository https://github.com/holon-platform/holon-datastore-jdbc.

See the repository README file for information about:

  • The source code structure.

  • How to build the module artifacts from sources.

  • Where to find the code examples.

  • How to contribute to the module development.

The SQL composition engine of JDBC Datastore API is designed to avoid and prevent SQL injection type attacks, since a meta-language is used for the Datastore operations definition a any provided parameter value is managed using JDBC PreparedStatement statements types.

3. Obtaining the artifacts

The Holon Platform uses Maven for projects build and configuration. All the platform artifacts are published in the Maven Central Repository, so there is no need to explicitly declare additional repositories in your project pom file.

At the top of each section of this documentation you will find the Maven coordinates (group id, artifact id and version) to obtain the artifact(s) as a dependency for your project.

A BOM (Bill Of Materials) pom is provided to import the available dependencies for a specific version in your projects. The Maven coordinates for the core BOM are the following:

Maven coordinates:

<groupId>com.holon-platform.jdbc</groupId>
<artifactId>holon-datastore-jdbc-bom</artifactId>
<version>5.1.2</version>

The BOM can be imported in a Maven project in the following way:

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>com.holon-platform.jdbc</groupId>
      <artifactId>holon-datastore-jdbc-bom</artifactId>
      <version>5.1.2</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

3.1. Using the Platform BOM

The Holon Platform provides an overall Maven BOM (Bill of Materials) to easily obtain all the available platform artifacts.

See Obtain the platform artifacts for details.

4. What’s new in version 5.1.x

  • Support of the the PropertySet identifier properties to detect the persistent entities primary keys avoiding additional database accesses. See Identifier resolution strategy.

  • Full support for date and time functions and for java.time.* temporal types. See Datastore API temporal functions support.

  • Technology-independent transactions support through the Transactional API. See Transactions management.

  • Complete and deep revision and rewriting of the internal SQL composer engine, which is now separated as an independent artifact (holon-datastore-jdbc-composer). This ensures more consistent operation resolution strategies, remarkable performance improvements and extensibility by design. See Extending the JDBC Datastore API.

  • Improved support for industry-standard vendors RDBMS, such as Oracle Database, Microsoft SQLServer, IBM DB2 and SAP HANA.

4.1. Migrating from version 5.0.x

4.1.1. Deprecations

  • JdbcDatastore Builder API: autoCommit. The default auto-commit mode setup for JDBC connections is deprecated in favor of the new transactional API support. Transactional operations should be used to manage connections auto-commit. See Transactions management.

4.1.2. Dialects

Because of the complete and deep revision and rewriting of the internal SQL composer engine, the package structure and class name is deeply changed. This not affects the public API in any way, only the concrete sql dialect implementations were relocated and the dialect class name is changed from JdbcDialect to SQLDialect.

The new dialect implementations can be found in the holon-datastore-jdbc-composer artifact, under the com.holonplatform.datastore.jdbc.composer.dialect package.

So if a dialect fully qualified class name was used to specify the JDBC Datastore dialect, it has to be replaced with the new SQLDialect implementation class.

4.1.3. SQL filter and sort

The com.holonplatform.datastore.jdbc.JdbcWhereFilter and com.holonplatform.datastore.jdbc.JdbcOrderBySort, which allow custom QueryFilter and QuerySort declarations directly providing the SQL WHERE and ORDER BY parts, are replaced with the WhereFilter and OrderBySort classes, located in the holon-datastore-jdbc-composer artifact.

The classes semantic and API is the same as before. See Custom SQL filters and sorts.

5. JDBC Datastore

The holon-datastore-jdbc artifact is the main entry point to use the JDBC Datastore API implementation.

Maven coordinates:

<groupId>com.holon-platform.jdbc</groupId>
<artifactId>holon-datastore-jdbc</artifactId>
<version>5.1.2</version>

The JdbcDatastore interface represents the JDBC Datastore API implementation, extending the core Datastore API.

The JdbcDatastore API, besides the standard Datastore API operations, provides methods to:

  • Create and configure a JdbcDatastore API instance, using the provided builder.

  • Directly working with JdbcDatastore managed connections, represented by the standard JDBC connection interface (java.sql.Connection). See JdbcDatastore API.

If you want to reach the goal of a complete abstraction from the persistence store technology and the persistence model, the core Datastore API interface should be used instead of the specific JdbcDatastore API by your application code. This way, the concrete Datastore API implementation may be replaced by a different one at any time, without any change to the codebase.

5.1. Setup and configuration

To create a JDBC Datastore instance, the builder() static method of the JdbcDatastore API can be used to obtain the JDBC Datastore builder API.

The JDBC Datastore builder provides a JdbcDatastore instance:

JdbcDatastore datastore = JdbcDatastore.builder() (1)
    // Datastore configuration omitted
    .build();
1 Obtain the JDBC Datastore builder to configure and create a new JDBC Datastore instance

But, as stated in the previous section, to reach the goal of a complete abstraction from the persistence store technology and the persistence model, the core Datastore API interface should be used by your application code, instead of the specific JdbcDatastore API.

So you can simply obtain the JDBC Datastore implementation as a core Datastore API implementation:

Datastore datastore = JdbcDatastore.builder() (1)
    // Datastore configuration omitted
    .build();
1 Obtain the JDBC Datastore builder to configure and create a new JDBC Datastore instance and expose it as core Datastore API type

5.1.1. Common Datastore configuration options

The JDBC Datastore builder API extends the core Datastore builder API, which provides common Datastore configuration settings as listed below.

Builder method Arguments Description

dataContextId

The data context id String value

Set the data context id to which the Datastore is bound. Can be used, for example, to declare configuration properties for multiple Datastore instances. See the Multiple Datastores configuration documentation section.

traceEnabled

true or false

Whether to enable Datastore operations tracing. When enabled, the JDBC Datastore will log any SQL operation performed using the Datastore API.

configuration

A DatastoreConfigProperties instance

Set the DatastoreConfigProperties type configuration property set instance to use in order to read the Datastore configuration properties. See the Datastore configuration documentation section for details. This configuration properties can be used as an alternative for the programmatic configuration performed with the previous builder methods.

Example of base JDBC Datastore configuration:

Datastore datastore = JdbcDatastore.builder()
    // DataSource configuration omitted
    .dataContextId("mydataContextId") (1)
    .traceEnabled(true) (2)
    .build();
1 Set a data context id for the Datastore
2 Activate operations tracing in log

The configuration properties can also be provided through an external configuration property source, using the properties provided by the DatastoreConfigProperties property set.

For example, supposing to have a properties file named datastore.properties like this:

holon.datastore.trace=true

We can use it as configuration property source to enable the Datastore tracing mode:

Datastore datastore = JdbcDatastore.builder()
    // DataSource configuration omitted
    .configuration(DatastoreConfigProperties.builder().withPropertySource("datastore.properties").build()) (1)
    .build();
1 Use the datastore.properties file as configuration property source

5.1.2. DataSource configuration

The JDBC Datastore implementation relies on the javax.sql.DataSource API to access the concrete data store using JDBC, and the DataSource instance to be used must be provided at JDBC Datastore configuration time.

The DataSource reference is the only required JDBC Datastore configuration attribute and can be provided in two ways:

1. Direct:

The concrete DataSource implementation can be provided using the JDBC Datastore builder, through the dataSource(DataSource dataSource) method.

DataSource datasource = createOrObtainDatasource();

Datastore datastore = JdbcDatastore.builder() //
    .dataSource(datasource) (1)
    .build();
1 Set the DataSource instance to use

2. Indirect:

A DataSource instance can be otained using the Holon Platform JDBC module DataSource configuration facilities through a set of configuration properties, represented by the DataSourceConfigProperties property set.

See the JDBC module DataSource configuration properties documentation to learn about the available DataSource configuration properties.

A DataSourceConfigProperties instance can be loaded using the configuration property providers API and provided to the JDBC Datastore builder.

For example, supposing to have a properties file named datasource.properties like this:

holon.datasource.url=jdbc:h2:mem:test
holon.datasource.username=sa

The JDBC Datastore instance can be created in the following way:

Datastore datastore = JdbcDatastore.builder() //
    .dataSource(DataSourceConfigProperties.builder().withPropertySource("datasource.properties").build()) (1)
    .build();
1 A DataSource instance will be created and configured for the JDBC Datastore using the DataSource configuration properties loaded from the datasource.properties file
See the DataSource configuration documentation section of the Holon Platform JDBC module for detailed information about the DataSource creation and configuration APIs and strategies.

5.1.3. Database platform configuration

For some internal operations, the JDBC Datastore needs to know the concrete Database platform to which the DataSource instance is bound (for example H2, MySQL and so on). The Database platform is used, for example, to auto-detect the SQL dialect to use if not directly specified at JDBC Datastore configuration time.

The Database platform can be explicitly specified either using:

  • The JDBC Datastore database builder method, using the DatabasePlatform enumeration.

Datastore datastore = JdbcDatastore.builder() //
    .dataSource(createOrObtainDatasource()) //
    .database(DatabasePlatform.H2) (1)
    .build();
1 Database platform specification

  • Or the holon.datasource.platform configuration property, if provided in the DataSource configuration property set when using the indirect DataSource instance configuration, as described in the previous section.

Database platform auto detection:

When the Database platform is not explicitly specified, the JDBC Datastore will try to auto-detect it, inspecting the JDBC connection URL of the provided DataSource instance.

5.1.4. SQL Dialect configuration

To ensure operations consistency and efficiency, the JDBC Datastore uses the SQLDialect API abstraction in order to resolve each database platform specificity and SQL language difference.

Normally, the SQLDialect implementation to use is auto-detected by the JDBC Datastore, relying on the Database platform to which the DataSource instance is bound, as described in the previous section.

The SQLDialect implementation to use can be also explicitly configured using the JDBC Datastore builder. This can be done in two ways:

1. SQLDialect configuration using the JDBC Datastore builder:

The SQL dialect to use can be directly configured using the JDBC Datastore builder, using the dialect(SQLDialect dialect) or the dialect(String dialectClassName) method.

The SQLDialect API provides a static methods to obtain the SQLDialect for a specific database platform or to directly obtain a specific dialect implementation within the available ones.

Datastore datastore = JdbcDatastore.builder() //
    .dataSource(createOrObtainDatasource()) //
    .dialect(SQLDialect.h2()) (1)
    .dialect("com.holonplatform.datastore.jdbc.composer.dialect.H2Dialect") (2)
    .build();
1 Configure the dialect using a specific dialect implementation
2 Configure the dialect using the dialect class name

1. SQLDialect configuration using a configuration property:

The SQL dialect to use can be also configured using the default holon.datastore.dialect Datastore configuration property, available from the DatastoreConfigProperties property set.

The fully qualified dialect class name must be provided as property value.

For example, supposing to have a properties file named datastore.properties like this:

holon.datastore.dialect=com.holonplatform.datastore.jdbc.composer.dialect.H2Dialect
holon.datastore.trace=true

We can use it as configuration property source to configure the JDBC Datastore dialect:

Datastore datastore = JdbcDatastore.builder() //
    .dataSource(createOrObtainDatasource()) //
    .configuration(DatastoreConfigProperties.builder().withPropertySource("datastore.properties").build()) (1)
    .build();
1 Use the datastore.properties file as configuration property source

5.1.5. Builtin SQL dialects

The Holon JDBC Datastore module provides a set of builtin SQL dialects for the most common database platforms. The currently available SQL dialect implementations are:

Database platform Dialect class Supported versions

DB2

DB2Dialect

8 and higher

Derby

DerbyDialect

10.5 and higher

H2

H2Dialect

1.4 and higher

HyperSQL (HSQLDB)

HSQLDialect

2.0.0 and higher

Informix

InformixDialect

11 and higher

MySQL

MySQLDialect

4.1 and higher

MariaDB

MariaDBDialect

5.5 and higher

Oracle Database

OracleDialect

9i and higher

PostgreSQL

PostgreSQLDialect

8.2.5 and higher

Microsoft SQL Server

SQLServerDialect

2005 or higher

SAP HANA

HANADialect

1.0 SPS12 and higher

SQLite

SQLiteDialect

3.0.7 and higher

5.1.6. Identifier resolution strategy

For some of its internal operations, the JDBC Datastore needs to know the actual table primary key to ensure consistency, for example for the save Datastore API operation, which performs an insert type operation if a row is not present or an update type operation otherwise.

Any standard Datastore API operation relies on the Holon Platform property model to represent the data model, using the PropertyBox API to receive and provide the data model attributes values.

To ensure consistency for operations which have to identify a PropertyBox instance against the concrete data model (in the JDBC world, the row of a table), the JDBC Datastore needs to know which properties of the PropertyBox property set have to be considered as identifier properties, if any. This way, the identifier property values can be used to implement a consistent strategy to map the PropertyBox instances to the proper table rows.

The JDBC Datastore identifier resolution strategy defines how this is accomplished, and it is represented by the IdentifierResolutionStrategy enumeration.

The available identifier resolution strategies are:

Strategy Description

IDENTIFIER_PROPERTIES

Use the PropertySet identifier properties as PropertyBox identifier properties. See PropertySet identifier properties for details.

TABLE_PRIMARY_KEY

Use the database table primary key to obtain the PropertyBox identifier properties.

AUTO

Use the IDENTIFIER_PROPERTIES strategy when the PropertyBox property set provides configured identifier properties, otherwise use the TABLE_PRIMARY_KEY strategy.

The AUTO identifier resolution strategy is the default strategy adopted by the JDBC Datastore.

To configure a specific identifier resolution strategy, the JDBC Datastore builder API can be used, through the identifierResolutionStrategy method.

Datastore datastore = JdbcDatastore.builder() //
    .dataSource(createOrObtainDatasource()) //
    .identifierResolutionStrategy(IdentifierResolutionStrategy.TABLE_PRIMARY_KEY) (1)
    .build();
1 Set the identifier resolution strategy to TABLE_PRIMARY_KEY

5.1.7. JDBC connection handler

The JDBC Datastore builder allows to configure the JDBC connection lifecycle through the JdbcConnectionHandler API.

When a custom implementation is provided, the getConnection and releaseConnection methods of the JdbcConnectionHandler API will be use to obtain a JDBC connection and to release it, respectively.

The default JDBC connection handler used by the JDBC Datastore simply uses the getConnection() method of the DataSource to obtain a connection and the Connection.close() method to release it.

Datastore datastore = JdbcDatastore.builder() //
    .dataSource(createOrObtainDatasource()) //
    .connectionHandler(new JdbcConnectionHandler() { (1)

      @Override
      public Connection getConnection(DataSource dataSource, ConnectionType connectionType)
          throws SQLException {
        // provide the JDBC connection
        return dataSource.getConnection();
      }

      @Override
      public void releaseConnection(Connection connection, DataSource dataSource,
          ConnectionType connectionType) throws SQLException {
        // release the JDBC connection
        connection.close();
      }

    }).build();
1 Configure a custom JdbcConnectionHandler for the JDBC Datastore

5.2. Data model attributes naming conventions

The JDBC Datastore relies on the following conventions regarding the mappings between the Holon Platform property model and the concrete JDBC data model (i.e. the RDMBS schema):

  • A DataTarget name is mapped to a RDBMS table (or view) name.

  • A Path name (and so a PathProperty path name) is mapped to a RDBMS table (or view) column name.

The SQLDialect in use could decide to apply some manipulation operations to the DataTarget or Path names in order to properly match the database schema elements names. For example, it could apply uppercase transformations if the undelying RDBMS only supports uppercase schema objects names.

For example, given a table definition as follows:

create table test (
  code numeric(20) primary key,
  text varchar(100)
)

The property model will be defined simply using the table and column names:

static final NumericProperty<Long> ID = NumericProperty.longType("code") (1)
    .validator(Validator.notNull());
static final StringProperty VALUE = StringProperty.create("text") (2)
    .validator(Validator.max(100));

static final PropertySet<?> TEST = PropertySet.builderOf(ID, VALUE).identifier(ID).build(); (3)

static final DataTarget<?> TARGET = DataTarget.named("test"); (4)
1 Map the ID property to the code path name (i.e. the table column name)
2 Map the VALUE property to the text path name (i.e. the table column name)
3 The TEST PropertySet is the test table schema representation. Furthermore, the ID property is configured as the property set identifier property
4 The TARGET DataTarget is defined using the test name, which corresponds to the database table name

Now the Datastore API can be used to manage the test table data:

Datastore datastore = JdbcDatastore.builder().dataSource(createOrObtainDatasource()).build(); (1)

PropertyBox value = PropertyBox.builder(TEST).set(ID, 1L).set(VALUE, "One").build();
datastore.save(TARGET, value); (2)

Stream<PropertyBox> results = datastore.query().target(TARGET).filter(ID.goe(1L)).stream(TEST); (3)

List<String> values = datastore.query().target(TARGET).sort(ID.asc()).list(VALUE); (4)

datastore.bulkDelete(TARGET).filter(ID.gt(0L)).execute(); (5)
1 Create a JDBC Datastore API instance
2 Save a test table row (insert if not exists, update otherwise) with the given property values
3 Query the test table where the ID property value (i.e. the code table column value) is greater or equal to 1 and obtain the table rows as a Stream of PropertyBox values
4 Query the test table and obtain a list of the VALUE property values (i.e. the text table column value), ordering ascending by the ID property value
5 Execute a bulk delete operation, removing all the rows with the ID property value (i.e. the code table column value) greater than 0

5.2.1. Data path mappings

The JDBC Datastore fully supports the DataMappable API, which can be used to provide a mapping between a data related object path name and the actual path name to be used with the concrete data model schema.

When the getDataPath() method of a DataMappable type object returns a non empty value, such value will be used as actual data path, i.e. as RDBMS schema object name, instead of the default path name with which the object was configured.

StringProperty PROPERTY = StringProperty.create("propertyName").dataPath("str"); (1)
1 In this case, the str table column name will be used instead of propertyName when the property is involved in persistence related JDBC Datastore operations

This can be useful, for example, when an existing data model representation wants to used with a JDBC Datastore and the path property names do not match the actual RDBMS data model schema names.

As an example, we suppose to have a JPA entity model definition that we want to use as property model definition with a JDBC Datastore implementation.

If we don’t want to define a brand new property model, through a PathProperty set declaration, the Bean introspection API can be used to obtain a BeanPropertySet from the JPA entity definitions. But this way the PathProperty path names of the BeanPropertySet will be the JPA entity Bean property names, and it is not assured that they match the RDBMS schema objects names. In particular, if the @Column(name="xxx") is used on the Bean properties.

The data path mapping can be used to provide the actual data attribute name for the properties of the bean property set, in this case using the name attribute of the JPA @Column annotation.

We can use the Holon Platform JPA module to automatically map the name attribute of the JPA @Column annotation in the corresponding data path value of the bean property set PathProperty. Just ensure that the holon-jpa-bean-processors artifact is present in classpath.

At this point, the bean introspection API will use the provided JPA bean post processors to automatically configure the data path mapping in the properties, and the JDBC Datastore API can be seamlessy used, without any additional configuration.

For example, given the following JPA entity definition:

@Entity @Table(name = "test") class MyEntity {

  public static final BeanPropertySet<MyEntity> PROPERTIES = BeanPropertySet.create(MyEntity.class); (1)

  public static final DataTarget<MyEntity> TARGET = BeanDataTarget.of(MyEntity.class); (2)

  @Id
  @Column(name = "code")
  private Long id;

  @Column(name = "text")
  private String value;

  // getters and setters omitted

}
1 Create a BeanPropertySet using the entity class
2 Create a DataTarget for the entity class: the name attribute of the JPA @Table annotation will be used to configure a data path for the bean data target using the test table name

Since the name attribute of the JPA @Column annotations will be setted as data path property values at bean introspection time, the BeanPropertySet properties can be now used with a JDBC Datastore API just like in the previous example:

Datastore datastore = JdbcDatastore.builder().dataSource(createOrObtainDatasource()).build(); (1)

PropertyBox value = PropertyBox.builder(MyEntity.PROPERTIES) //
    .set(MyEntity.PROPERTIES.property("id"), 1L) //
    .set(MyEntity.PROPERTIES.property("value"), "One").build();
datastore.save(MyEntity.TARGET, value); (2)

Stream<PropertyBox> results = datastore.query().target(MyEntity.TARGET)
    .filter(MyEntity.PROPERTIES.property("id").goe(1L)).stream(MyEntity.PROPERTIES); (3)
1 Create a JDBC Datastore API instance
2 Save a test table row (insert if not exists, update otherwise) with the given property values
3 Query the test table where the id property value (i.e. the code table column value) is greater or equal to 1 and obtain the table rows as a Stream of PropertyBox values

5.3. SQL data types mapping

When the Java type is serialized as a SQL data type (for example when used as query parameter) or a SQL data type is deserialized as a Java type (for example to map it as a Property value), the JDBC conventions are used to perform the type mapping.

When a SQL type has not a direct Java type representation, the following conventions are used:

Table 1. SQL types mapping
SQL type Supported Java types

CLOB

java.lang.String, java.io.Reader

BLOB

byte[], java.io.InputStream
Table 2. Java types mapping
Java type SQL type Notes

java.lang.Enum

INTEGER

By default, the ordinal enum value is used for the mapping

java.time.LocalDate

DATE

A specific SQL dialect could use a different data type and perform value manipulation if required by the specific SQL type semantic

java.time.LocalTime

TIME

A specific SQL dialect could use a different data type and perform value manipulation if required by the specific SQL type semantic

java.time.LocalDateTime

TIMESTAMP

A specific SQL dialect could use a different data type and perform value manipulation if required by the specific SQL type semantic

5.4. Relational expressions

As relational Datastore, the JDBC Datastore API supports core relational expressions for data access and manipulation:

1. Sub-query:

The SubQuery interface can be used to represent a sub-query, which can be used in a query definition to express query restrictions (filters) that involve a sub-query as filter operand.

See the core sub query expression documentation for further information on sub query expressions.

2. Alias and Joins:

The RelationalTarget interface can be used to declare alias and joins for a DataTarget expression.

See the core alias and joins documentation for further information on alias and join expressions.

5.5. Auto-generated ids

The JDBC Datastore API supports the retrieving of auto-generated id column values, if supported by the JDBC driver in use.

The auto-generated id values can be obtained from the OperationResult object, returned by Datastore data manipulation operations, through the getInsertedKeys() and related methods.

Datastore datastore = getDatastore(); // build or obtain a JDBC Datastore

PropertyBox value = buildPropertyBoxValue();

OperationResult result = datastore.insert(DataTarget.named("test"), value); (1)

Map<Path<?>, Object> keys = result.getInsertedKeys(); (2)
Optional<Long> keyValue = result.getInsertedKey(ID); (3)
keyValue = result.getFirstInsertedKey(Long.class); (4)
1 Perform a insert type operation using the Datastore API
2 Get the auto-generated keys as a Map of key Path representation and key value
3 Get the auto-generated key value for the ID property, if available
4 Get the first auto-generated key value, if available, expecting it of Long type

The default BRING_BACK_GENERATED_IDS WriteOption can be provided to the Datastore API operation to bring back any auto-generated key value into the PropertyBox instance which was the subject of the operation, if a corresponding PathProperty (using the path name) is available in the PropertyBox property set.

final PathProperty<Long> KEY = PathProperty.create("key", Long.class); (1)
final PathProperty<String> TEXT = PathProperty.create("text", String.class);

Datastore datastore = getDatastore(); // build or obtain a JDBC Datastore

PropertyBox value = PropertyBox.builder(KEY, TEXT).set(TEXT, "test").build(); (2)

datastore.insert(DataTarget.named("tableName"), value, DefaultWriteOption.BRING_BACK_GENERATED_IDS); (3)

Long keyValue = value.getValue(KEY); (4)
1 The key column is supposed to be auto-generated by the database
2 Create the PropertyBox value to insert, not providing the key value
3 Perform the insert operation, providing the BRING_BACK_GENERATED_IDS write option
4 The KEY property value of the inserted PropertyBox is updated with the auto-generated key value, if available

5.6. Custom SQL filters and sorts

The JDBC Datastore API supports custom SQL filters and sorts expressions, i.e. QueryFilter and QuerySort type expressions for which the SQL statement that represents the WHERE and ORDER BY conditions is directly provided.

Since this kind of expressions accept SQL statements without performing any validation or parsing, you must pay maximum attention using them, since this way the code can be exposed to security concerns such as SQL injection type attacks.

5.6.1. WhereFilter

The WhereFilter interface is a QueryFilter representing a portion of the SQL WHERE clause expression.

QueryFilter whereFilter = WhereFilter.create("name='John'"); (1)

Stream<Long> results = getDatastore().query().target(TARGET).filter(whereFilter).stream(ID); (2)
1 Create a WhereFilter, providing the SQL statement to be included as is in the query WHERE clause
2 The QueryFilter can now be used in Datastore expressions just like any other filter expression

The WhereFilter expression supports query parameters, which must be expressed in the SQL statement using the default ? placeholder. The parameters values can be setted using the create WhereFilter builder method:

QueryFilter whereFilter = WhereFilter.create("name=?", "John"); (1)
1 Create a WhereFilter providing the SQL statement (using the ? parameter placeholder) and John as parameter value
The SQL ? parameter placeholders are replaced with the parameters values in the same order they are provided in the create WhereFilter builder method

5.6.2. OrderBySort

The OrderBySort interface is a QuerySort representing a portion of SQL ORDER BY clause expression.

An OrderBySort expression can be created using the create builder method.

QuerySort orderBySort = OrderBySort.create("id asc, name desc"); (1)

Stream<Long> results = getDatastore().query().target(TARGET).sort(orderBySort).stream(ID); (2)
1 Create a SQL order by expression to order by the id value ascending and the name value descending
2 The QuerySort can now be used in Datastore expressions just like any other sort expression

5.7. Transactions management

The JDBC Datastore API implementation is transactional, so it supports transactions management through the Transactional API, which can be used to manage transactions at a higher level, in an abstract and implementation-independent way.

See the Transactional Datastore documentation section for information on transactions management with the Transactional API.

final Datastore datastore = getDatastore(); // build or obtain a JDBC Datastore

datastore.requireTransactional().withTransaction(tx -> { (1)
  PropertyBox value = buildPropertyBoxValue();
  datastore.save(TARGET, value);

  tx.commit(); (2)
});

OperationResult result = datastore.requireTransactional().withTransaction(tx -> { (3)

  PropertyBox value = buildPropertyBoxValue();
  return datastore.save(TARGET, value);

}, TransactionConfiguration.withAutoCommit()); (4)
1 Obtain the Transactional API to execute one or more Datastore operation within a transaction
2 Commit the transaction
3 Obtain the Transactional API to execute the Datastore operation within a transaction and return a value
4 The transaction is configured with the auto commit mode, this way the transaction is automatically committed at the transactional operation end if no error occurred

5.8. JdbcDatastore API

The specialized JdbcDatastore API, which extends the standard Datastore API, makes available an additional methods through the ConnectionHandler interface to execute an operation using a Datastore managed JDBC connection.

The JDBC Datastore will take care of connection providing and finalization (i.e. connection closing operations).

JdbcDatastore datastore = getJdbcDatastore();

datastore.withConnection(connection -> { (1)
  // do something using the provided JDBC connection
  connection.createStatement();
});

String result = datastore.withConnection(connection -> { (2)
  // do something using the provided JDBC connection and return a result
  return null;
});
1 Execute an operation using a JDBC Datastore managed connection
2 Execute an operation using a JDBC Datastore managed connection and return a String type result
If you want to reach the goal of a complete abstraction from the persistence store technology and the persistence model, the core Datastore API interface should be used instead of the specific JdbcDatastore API by your application code. This way, the concrete Datastore API implementation may be replaced by a different one at any time, without any change to the codebase.

5.9. Extending the JDBC Datastore API

5.10. Expression resolvers

The Datastore API can be extended using the ExpressionResolver API, to add new expression resolution strategies, modify existing ones and to handle new Expression types.

See the Datastore API extension documentation section for details.

5.10.1. JDBC Expression resolvers registration

A new ExpressionResolver can be registered in the JDBC Datastore API in two ways:

1. Using the JDBC Datastore API instance:

An ExpressionResolver can be registered either using the Datastore builder API at Datastore configuration time:

Datastore datastore = JdbcDatastore.builder() //
    .withExpressionResolver(new MyExpressionResolver()) (1)
    .build();
1 Register and new ExpressionResolver

Or using the Datastore API itself, which extends the ExpressionResolverSupport API:

datastore.addExpressionResolver(new MyExpressionResolver()); (1)
1 Register and new ExpressionResolver

2. Automatic registration using Java service extensions:

The JDBC Datastore supports ExpressionResolver automatic registration using the JdbcDatastoreExpressionResolver base type and the default Java service extensions modality.

To automatically register an ExpressionResolver this way, a class implementing JdbcDatastoreExpressionResolver has to be created and its fully qualified name must be specified in a file named com.holonplatform.datastore.jdbc.config.JdbcDatastoreExpressionResolver, placed in the META-INF/services folder in classpath.

When this registration method is used, the expression resolvers defined this way will be registered for any JDBC Datastore API instance.

5.10.2. Specific expression resolvers registration

All the default Datastore API operation representations supports operation specific expression resolvers registration, through the ExpressionResolverSupport API.

An ExpressionResolver registered for a specific Datastore API operation execution will be available only for the execution of that operation, and will be ignored by any other Datastore API operation.

For example, to register an expression resolver only for a single Query execution, the Query builder API can be used:

long result = datastore.query().target(DataTarget.named("test")) //
    .withExpressionResolver(new MyExpressionResolver()) (1)
    .count();
1 Register an expression resolver only for the specific Query operation definition

5.10.3. Expression resolvers priority

According to the standard convention, the javax.annotation.Priority annotation can be used on ExpressionResolver classes to indicate in what order the expression resolvers bound to the same type resolution pair (i.e. the expression type handled by a resolver and the target expression type into which it will be resolved) must be applied.

The less is the javax.annotation.Priority number assigned to a resolver, the higher will be it’s priority order.

All the default JDBC Datastore expression resolvers have the minimum priority order, allowing to override their behavior and resolution strategies with custom expression resolvers with a higher assigned priority order (i.e. a priority number less then Integer.MAX_VALUE).

5.10.4. Expression validation

The internal JDBC Datastore SQL composer engine will perform validation on any Expression instance to resolve and each corresponding resolved Expression instance, using the default expression validate() method.

So the validate() method can be used to implement custom expression validation logic and throw an InvalidExpressionException when validation fails.

5.10.5. JDBC Datastore expressions

Besides the standard Datastore API expressions, such as DataTarget, QueryFilter and QuerySort, which can be used to extend the Datastore API with new expression implementations and new resolution strategies, the JDBC Datastore API can be extended using a set of specific SQL resolution expressions, used by the internal SQL composer engine to implement the resolution and composition strategy to obtain SQL statements from the Datastore API meta-language expressions.

These SQL expression are available from the com.holonplatform.datastore.jdbc.composer.expression package of the holon-datastore-jdbc-composer artifact.

The SQLExpression is the expression which represents an SQL statement part, used to compose the actual SQL statement which will be executed using the JDBC API. So this is the final target expression used by the SQL composer engine to obtain a SQL statement part from other, more abstract, expression types.

The SQLExpression type can be used to directly resolve an abstract Datastore API expression into a SQL statement part.

For example, supposing to have a KeyIs class which represents a QueryFilter expression type to represent the expression "the key column name value is equal to a given Long type value":

class KeyIs implements QueryFilter {

  private final Long value;

  public KeyIs(Long value) {
    this.value = value;
  }

  public Long getValue() {
    return value;
  }

  @Override
  public void validate() throws InvalidExpressionException {
    if (value == null) {
      throw new InvalidExpressionException("Kay value must be not null");
    }
  }

}

We want to create an ExpressionResolver class to resolve the KeyIs expression directly into a SQL WHERE statemet part, using the SQLExpression type. Using the convenience create method of the ExpressionResolver API, we can do it in the following way:

final ExpressionResolver<KeyIs, SQLExpression> keyIsResolver = ExpressionResolver.create( //
    KeyIs.class, (1)
    SQLExpression.class, (2)
    (keyIs, ctx) -> Optional.of(SQLExpression.create("key = " + keyIs.getValue()))); (3)
1 Expression type to resolve
2 Target expression type
3 Expression resolution logic: since we resolve the KeyIs expression directly into SQLExpression type, the SQL WHERE clause part is provide

After the ExpressionResolver is registered in the Datastore API, the new KeyIs expression can be used in the Datastore API operations which support the QueryFilter expression type just like any other filter expression. For exmaple, in a Query expression:

Datastore datastore = JdbcDatastore.builder().withExpressionResolver(keyIsResolver) (1)
    .build();

Query query = datastore.query().filter(new KeyIs(1L)); (2)
1 Register the new expression resolver
2 Use the KeyIs expression in a query definition

The SQL composer engine will translate the given KeyIs expression in the SQL WHERE statement part key = 1, using the previously defined expression resolver.

Other expression types are used to represent elements of a query or a Datastore operation, to be resolved into a final SQLExpression type. These expression types often represent an intermediate expression type, between the highest abstract layer (i.e. an expression of the Datastore API meta-language) and the final SQL statement part representation (i.e. the SQLExpression type).

Some examples are:

  • SQLLiteral to represent a literal value.

  • SQLParameter to represent a parameter value.

  • SQLFunction to represent a SQL function.

  • SQLProjection to represent a SQL SELECT projection.

  • SQLStatement to represent a full SQL statement with parameters support.

  • SQLQueryDefinition and SQLQuery to represent the definition of a SQL query and the query statement representation with the SQLResultConverter to use to covert the query results in the expected Java type.

For example, let’s see how the SQLFunction expression can be used as an intermediate SQL expression type to define a new SQL function.

We want to define a IfNull function, which returns a fallback value expression when a given expression is null, following the syntax of the MySQL IFNULL function.

We will use the QueryFunction expression type to represent the function, since it is the default function expression representation of the Datastore API.

public class IfNull<T> implements QueryFunction<T, T> {

  private final TypedExpression<T> nullableValue; (1)
  private final TypedExpression<T> fallbackValue; (2)

  public IfNull(TypedExpression<T> nullableValue, TypedExpression<T> fallbackValue) {
    super();
    this.nullableValue = nullableValue;
    this.fallbackValue = fallbackValue;
  }

  public IfNull(QueryExpression<T> nullableValue, T fallbackValue) { (3)
    this(nullableValue, ConstantExpression.create(fallbackValue));
  }

  @Override
  public Class<? extends T> getType() {
    return nullableValue.getType();
  }

  @Override
  public void validate() throws InvalidExpressionException { (4)
    if (nullableValue == null) {
      throw new InvalidExpressionException("Missing nullable expression");
    }
    if (fallbackValue == null) {
      throw new InvalidExpressionException("Missing fallback expression");
    }
  }

  @Override
  public List<TypedExpression<? extends T>> getExpressionArguments() { (5)
    return Arrays.asList(nullableValue, fallbackValue);
  }

}
1 The nullable expression representation
2 The fallback expression representation to be returned when the first expression value is null
3 Convenience constructor to accept a constant expression value as fallback expression
4 Validate the arguments
5 The two function arguments will be the nullable expression and the fallback expression

Now we create an expression resolver to resolve the QueryFunction expression into a SQLFunction intermediate SQL expression type:

public class IfNullResolver implements ExpressionResolver<IfNull, SQLFunction> {

  @Override
  public Optional<SQLFunction> resolve(IfNull expression, ResolutionContext context)
      throws InvalidExpressionException {
    return Optional.of(SQLFunction.create(args -> { (1)
      StringBuilder sb = new StringBuilder();
      sb.append("IFNULL(");
      sb.append(args.get(0));
      sb.append(",");
      sb.append(args.get(1));
      sb.append(")");
      return sb.toString();
    }));
  }

  @Override
  public Class<? extends IfNull> getExpressionType() {
    return IfNull.class;
  }

  @Override
  public Class<? extends SQLFunction> getResolvedType() {
    return SQLFunction.class;
  }

}
1 Use the SQLFunction create method to provide the SQL function representation using the function arguments. The function arguments are already provided by the SQL composition engine as serialized SQL expression tokens, according to the actual arguments expression types

Now the function can be registered in the Datastore API and used the same way as any other QueryFunction expression implementation.

final StringProperty STR = StringProperty.create("str");
final DataTarget<?> TARGET = DataTarget.named("test");

Datastore datastore = JdbcDatastore.builder() //
    .withExpressionResolver(new IfNullResolver()) (1)
    .build();

Stream<String> values = datastore.query(TARGET).stream(new IfNull<>(STR, "(fallback)")); (2)
1 Register the IfNull function expression resolver in Datastore
2 The IfNull function is used to provide a fallback (fallback) value in a query projection for the STR String property value

5.10.6. JDBC Expression resolution context

The JDBC Datastore API makes available an extension of the standard expression ResolutionContext, to provide a set of configuration attributes and SQL resolution context specific operations. This resolution context extension is represented by the SQLCompositionContext API.

When used within the JDBC Datastore API, the ResolutionContext provided to the registered expresion resolvers is SQLCompositionContext for any JDBC Datastore API standard operation. To obtain a SQLCompositionContext, the isSQLCompositionContext method can be used.

The SQLStatementCompositionContext API is a further context extension which provides methods related to SQL statements composition. It can be obtained from a SQLCompositionContext through the isStatementCompositionContext() method.

@Override
public Optional<SQLExpression> resolve(SQLExpression expression, ResolutionContext context) (1)
    throws InvalidExpressionException {

  SQLCompositionContext.isSQLCompositionContext(context).ifPresent(ctx -> { (2)
    SQLDialect dialect = ctx.getDialect(); (3)

    ctx.isStatementCompositionContext().ifPresent(sctx -> { (4)
      sctx.addNamedParameter(SQLParameter.create("test", String.class)); (5)
    });
  });

  return Optional.empty();
}
1 Let’s suppose we are implementing an expression resolver resolution method
2 Check and obtain the current ResolutionContext as a SQLCompositionContext
3 As an example, the current SQLDialect is requested
4 If the context is a SQL statement resolution context, it can be obtained as a SQLStatementCompositionContext
5 Add a named parameter to the current SQL statement context

5.11. Commodity factories

The JDBC Datastore API supports Datastore commodities registration using the JdbcDatastoreCommodityFactory type.

See the Datastore commodities definition and registration documentation section to learn how the Datastore commodity architecture can be used to provide extensions to the default Datastore API.

The JdbcDatastoreCommodityFactory type provides a specialized JdbcDatastoreCommodityContext API as Datastore commodity context, to make available a set of JDBC Datastore specific configuration attributes and references, for example:

  • The DataSource instance used by the JDBC Datastore.

  • The configured (or auto-detected) SQL dialect.

  • The configured (or auto-detected) database platform.

  • The configured identifier resolution strategy.

  • The available expression resolvers

  • A set of APIs and configuration methods available from the SQL composer engine.

Furthermore, it makes available some API methods to invoke some JDBC Datastore operations, such as the withConnection(ConnectionOperation<R> operation) method to execute an operation using a Datastore managed JDBC connection or methods to inspect and create other Datastore commodities.

interface MyCommodity extends DatastoreCommodity { (1)

  DatabasePlatform getPlatform();

}

class MyCommodityImpl implements MyCommodity { (2)

  private final DatabasePlatform platform;

  public MyCommodityImpl(DatabasePlatform platform) {
    super();
    this.platform = platform;
  }

  @Override
  public DatabasePlatform getPlatform() {
    return platform;
  }

}

class MyCommodityFactory implements JdbcDatastoreCommodityFactory<MyCommodity> { (3)

  @Override
  public Class<? extends MyCommodity> getCommodityType() {
    return MyCommodity.class;
  }

  @Override
  public MyCommodity createCommodity(JdbcDatastoreCommodityContext context)
      throws CommodityConfigurationException {
    // examples of configuration attributes:
    DataSource dataSource = context.getDataSource();
    SQLDialect dialect = context.getDialect();
    return new MyCommodityImpl(context.getDatabase().orElse(DatabasePlatform.NONE));
  }

}
1 Datastore commodity API
2 Commodity implementation
3 Commodity factory implementation

A Datastore commodity factory class which extends the JdbcDatastoreCommodityFactory interface can be registered in a JDBC Datastore in two ways:

1. Direct registration using the JDBC Datastore API builder:

The JDBC Datastore API supports DatastoreCommodityFactory automatic registration using the JdbcDatastoreCommodityFactory type using a Java service extensions based registration method.

Datastore datastore = JdbcDatastore.builder() //
    .withCommodity(new MyCommodityFactory()) (1)
    .build();
1 Register the MyCommodityFactory commodity factory in given JDBC Datastore implementation

2. Automatic registration using the Java service extensions:

To automatically register an commodity factory using the standard Java service extensions based method, a class implementing JdbcDatastoreCommodityFactory has to be created and its qualified full name must be specified in a file named com.holonplatform.datastore.jdbc.config.JdbcDatastoreCommodityFactory, placed in the META-INF/services folder of the classpath.

When this registration method is used, the commodity factories defined this way will be registered for any JDBC Datastore API instance.

6. Spring ecosystem integration

The holon-datastore-jdbc-spring artifact provides integration with the Spring framework for the JDBC Datastore API.

Maven coordinates:

<groupId>com.holon-platform.jdbc</groupId>
<artifactId>holon-datastore-jdbc-spring</artifactId>
<version>5.1.2</version>

6.1. Integration with the Spring JDBC infrastructure

When a JDBC Datastore API is configured as a Spring bean using the facilities described in this documentation section, a consistent integration with the Spring JDBC infrastructure is automatically provided.

In particular, the JDBC connection handler used by the Spring JDBC Datastore API implementations in fully integrated with the Spring JDBC infrastructure, for example regarding the current Connection and transaction synchronization support.

This way, the JDBC Datastore API can be seamlessly used along with the Spring JDBC and transactions management conventions, for example when using a Spring PlatformTransactionManager or the @Transactional annotation.

6.2. JDBC Datastore configuration

The EnableJdbcDatastore annotation can be used on Spring configuration classes to enable automatic JDBC Datastore beans configuration.

By default, the JDBC Datastore bean name configured with the @EnableJdbcDatastore annotation will be jdbcDatastore.

6.2.1. DataSource

The DataSource bean to be used to configure the JDBC Datastore API is obtained as follows:

  • If the dataSourceReference attribute of the @EnableJdbcDatastore is setted, the provided bean definition name will be used as the DataSource bean definition name to use.

@EnableJdbcDatastore(dataSourceReference = "myDataSource") (1)
@Configuration
class Config {

  @Bean(name = "myDataSource")
  public DataSource myDataSource() {
    return buildDataSource();
  }

}

@Autowired
Datastore datastore; (2)
1 Provide the DataSource bean definition name to use with the JDBC Datastore
2 The JDBC Datastore is configured and made available, for example, using dependency injection

  • Otherwise, the default dataSource bean definition name will be used to lookup for the DataSource bean to use.

 
@EnableJdbcDatastore
@Configuration
class Config {

  @Bean
  public DataSource dataSource() { (1)
    return buildDataSource();
  }

}

@Autowired
Datastore datastore; (2)
1 The default dataSource bean definition name is used for the DataSource bean definition
2 The JDBC Datastore is configured and made available, for example, using dependency injection

If a DataSource bean definition whith the required name is not present in Spring context, an initialization error is thrown.

You can use the @EnableDataSource provided by the Holon Platform JDBC Module to auto configure the DataSource bean to be used with the JDBC Datastore. 
@EnableDataSource (1)
@EnableJdbcDatastore (2)
@PropertySource("jdbc.properties") (3)
@Configuration
class Config {

}

@Autowired
DataSource dataSource;

@Autowired
Datastore datastore;
1 Use the @EnableDataSource annotation to configure a DataSource bean using the Spring environment configuration properties
2 Use the @EnableJdbcDatastore annotation to configure a JDBC Datastore bean backed by the previously configured DataSource
3 Configuration properties source

6.2.2. Multiple JDBC Datastores configuration

When more than one JDBC Datastore bean has to be configured using the @EnableJdbcDatastore annotation, the dataContextId attribute can be used to assign a different data context id to each JDBC Datastore bean definition, in order to:

  • Provide different sets of configuration properties using the same Spring environment.

  • Provide a default name pattern matching strategy with the DataSource bean definition to use for each JDBC Datastore to configure: if not directly specified with the dataSourceReference attribute, the DataSource bean definition to use for each JDBC Datastore will be detected in Spring context using the bean name pattern: dataSource_{datacontextid} where {datacontextid} is equal to the dataContextId attribute of the @EnableJdbcDatastore annotation.

When a data context id is defined, a Spring qualifier named the same as the data context id will be associated to the generated JDBC Datastore bean definitions, and such qualifier can be later used to obtain the right Datastore instance through dependency injection.

Furthermore, the JDBC Datastore bean definitions will be named using the data context id as suffix, according to the name pattern: jdbcDatastore_{datacontextid}.

@Configuration class Config {

  @Configuration
  @EnableJdbcDatastore(dataContextId = "one") (1)
  static class Config1 {

    @Bean(name = "dataSource_one")
    public DataSource dataSource() {
      return buildDataSource();
    }

  }

  @Configuration
  @EnableJdbcDatastore(dataContextId = "two") (2)
  static class Config2 {

    @Bean(name = "dataSource_two")
    public DataSource dataSource() {
      return buildDataSource();
    }

  }

}

@Autowired
@Qualifier("one")
Datastore datastore1; (3)

@Autowired
@Qualifier("two")
Datastore datastore2;
1 Configure the first JDBC Datastore using one as data context id: by default the bean named dataSource_one will be used as DataSource
2 Configure the first JDBC Datastore using two as data context id: by default the bean named dataSource_two will be used as DataSource
3 A specific Datastore type bean reference can be obtained using the data context id as qualifier

When using the @EnableDataSource provided by the Holon Platform JDBC Module to auto configure the DataSource bean, a matching data context id value can be provided to match the JDBC Datastore beans with the corresponding DataSource beans.

For example, given a jdbc.properties configuration property source file defined as follows:

holon.datasource.one.url=jdbc:h2:mem:testdbm1
holon.datasource.one.username=sa

holon.datasource.two.url=jdbc:h2:mem:testdbm2
holon.datasource.two.username=sa

The @EnableDataSource and @EnableJdbcDatastore annotations can be used to configure two DataSource/Datastore pairs, one using the one data context id and the other using the two data context id:

@Configuration
@PropertySource("jdbc.properties")
static class Config {

  @Configuration
  @EnableDataSource(dataContextId = "one")
  @EnableJdbcDatastore(dataContextId = "one")
  static class Config1 {
  }

  @Configuration
  @EnableDataSource(dataContextId = "two")
  @EnableJdbcDatastore(dataContextId = "two")
  static class Config2 {
  }

}

@Autowired
@Qualifier("one")
DataSource dataSource1;
@Autowired
@Qualifier("one")
Datastore datastore1;

@Autowired
@Qualifier("two")
DataSource dataSource2;
@Autowired
@Qualifier("two")
Datastore datastore2;

6.2.3. Database platform

By default, the database platform to which the DataSource is bound is auto-detected by the JDBC Datastore inspecting the JDBC connection URL (see Database platform configuration).

The database platform is used by the JDBC Datastore to select the most suitable SQL Dialect to use, if not otherwise specified.

To explicitly specify a database platform, the platform attribute of the @EnableJdbcDatastore annotation can be used.

@EnableJdbcDatastore(platform = DatabasePlatform.H2) (1)
@Configuration
class Config {

  // ...

}
1 Explicitly set H2 as database platform

6.2.4. Identifier resolution strategy

The the identifierResolutionStrategy attribute of the @EnableJdbcDatastore annotation can be used to specify identifier resolution strategy to use with the configured JDBC Datastore.

See the Identifier resolution strategy section for information about the identifier resolution strategies.

6.2.5. Transactional JDBC Datastore operations

The transactional attribute of the @EnableJdbcDatastore annotation can be used to control the transactional configuration of a set of the Datastore API operations.

When setted to true, the Spring @Transactional annotation behavior is automatically added to the following Datastore API operation methods:

  • refresh

  • insert

  • update

  • save

  • delete

The default REQUIRED propagation behavior is used, thus allowing the method calls to participate in an existing transaction or to be executed in a new one when the Spring transactions infrastructure is used.

The transactional attribute is true by default 
@EnableDataSource
@EnableJdbcDatastore
@PropertySource("jdbc.properties")
@EnableTransactionManagement (1)
@Configuration
class Config {

}

@Autowired
Datastore datastore;

void doTransactionally() {
  datastore.insert(DataTarget.named("test"), buildPropertyBoxValue()); (2)
}
1 Enables Spring’s annotation-driven transaction management capability.
2 The insert method is transactional by default, so the @Transactional annotation is not explicitly required here

The transactional attribute can be used to disable this default behavior:

@EnableJdbcDatastore(transactional = false)
@Configuration
class Config {

}

6.2.6. Primary mode

The @EnableJdbcDatastore annotation provides a primary() attribute which can be used to control the primary mode of the JDBC Datastore bean registration.

If the primary mode is set to PrimaryMode.TRUE, the Datastore bean created with the corresponding annotation will be marked as primary in the Spring application context, meaning that will be the one provided by Spring in case of multiple available candidates, when no specific bean name or qualifier is specified in the dependency injection declaration.

This behaviour is similar to the one obtained with the Spring @Primary annotation at bean definition time.

By default, the primary mode is set to PrimaryMode.AUTO, meaning that the registred JDBC Datastore bean will be marked as primary only when the DataSource bean to which is bound is registered as primary candidate bean.

6.2.7. JDBC Datastore configuration properties

When a JDBC Datastore bean is configured using the @EnableJdbcDatastore annotation, the Spring environment is automatically used as configuration properties source.

This way, many Datastore configuration settings can be provided using a configuration property with the proper name and value.

The supported configuration properties are:

1. The standard Datastore configuration properties, avaible from the DatastoreConfigProperties property set (See Datastore configuration).

The configuration property prefix is holon.datastore and the following properties are available:

Table 3. Datastore configuration properties
Name Type Meaning

holon.datastore. trace

Boolean (true / false)

Enable/disable Datastore operations tracing.

holon.datastore. dialect

String

The fully qualified class name of the SQL Dialect to use. See SQL Dialect configuration.

2. An additional set of properties, provided by the JdbcDatastoreConfigProperties property set, which can be used as an alternative for the @EnableJdbcDatastore annotation attributes described in the previous sections.

Table 4. JDBC Datastore configuration properties
Name Type Meaning

holon.datastore.jdbc. platform

A valid String which identifies one of the platform names listed in the DatabasePlatform enumeration.

Set the database platform to which the Datastore is bound.

holon.datastore.jdbc. primary

Boolean (true / false)

Mark the JDBC Datastore bean as primary candidate for dependency injection when more than one definition is available. IF not setted to true, the AUTO strategy will be used: the JDBC Datastore bean will be marked as primary only when the DataSource bean to which is bound is registered as primary candidate bean.

holon.datastore.jdbc. identifier-resolution-strategy

A valid String which identifies one of the strategy names listed in the IdentifierResolutionStrategy enumeration.

Set the JDBC Datastore identifier resolution strategy. See Identifier resolution strategy.

holon.datastore.jdbc. transactional

Boolean (true / false)

Whether to add the Spring @Transactional behavior to th suitable Datastore API methods. See Transactional JDBC Datastore operations.

Example of Datastore configuration properties:

holon.datastore.trace=true (1)
holon.datastore.dialect=my.dialect.class.Name (2)

holon.datastore.jdbc.platform=H2 (3)
holon.datastore.jdbc.identifier-resolution-strategy=TABLE_PRIMARY_KEY (4)
holon.datastore.jdbc.transactional=false (5)
1 Enable tracing
2 Set the dialect class name
3 Set the database platform
4 Use the TABLE_PRIMARY_KEY identifier resolution strategy
5 Disable the automatic transactional behavior of the Datastore operations

6.2.8. Datastore extension and configuration using the Spring context

The JDBC Datastore implementation supports the standard Holon Platform Datastore Spring integration features for Datastore beans configuration and extension, which includes:

@DatastoreResolver (1)
class MyFilterExpressionResolver implements QueryFilterResolver<MyFilter> {

  @Override
  public Class<? extends MyFilter> getExpressionType() {
    return MyFilter.class;
  }

  @Override
  public Optional<QueryFilter> resolve(MyFilter expression, ResolutionContext context)
      throws InvalidExpressionException {
    // implement actual MyFilter expression resolution
    return Optional.empty();
  }

}

@Component
class MyDatastorePostProcessor implements DatastorePostProcessor { (2)

  @Override
  public void postProcessDatastore(Datastore datastore, String datastoreBeanName) {
    // configure Datastore
  }

}

@DatastoreCommodityFactory (3)
class MyCommodityFactory implements JdbcDatastoreCommodityFactory<MyCommodity> {

  @Override
  public Class<? extends MyCommodity> getCommodityType() {
    return MyCommodity.class;
  }

  @Override
  public MyCommodity createCommodity(JdbcDatastoreCommodityContext context)
      throws CommodityConfigurationException {
    // create commodity instance
    return new MyCommodity();
  }

}
1 Automatically register a Datastore expression resolver using the @DatastoreResolver annotation
2 Post process Datastore configuration using a DatastorePostProcessor type Spring bean
3 Automatically register a Datastore commodity factory using the @DatastoreCommodityFactory annotation

7. Spring Boot integration

The holon-datastore-jdbc-spring-boot artifact provides integration with Spring Boot for JDBC Datastores auto-configuration.

To enable Spring Boot JDBC Datastore auto-configuration features, the following artifact must be included in your project dependencies:

Maven coordinates:

<groupId>com.holon-platform.jdbc</groupId>
<artifactId>holon-datastore-jdbc-spring-boot</artifactId>
<version>5.1.2</version>

A JDBC datastore is auto-configured only when:

  • A JdbcDatastore type bean is not already available from the Spring application context.

  • A valid DataSource type bean is available from the Spring application context.

The holon-datastore-jdbc-spring-boot declares as dependency the holon-jdbc-spring-boot artifact, which provides Spring Boot auto-configuration features for DataSource type beans made available from the Holon Platform JDBC Module.

For example, given an application.yml configuration file as follows:

holon:
  datasource:
    url: "jdbc:h2:mem:test"
    username: "sa"

  datastore:
    trace: true

The Holon platform Spring Boot auto-configuration classes will auto configure:

  • A DataSource type bean using the provided holon.datasource.* configuration properties.

  • A JDBC Datastore type bean backed by such DataSource, enabling operations tracing according to the holon.datastore.trace property value.

@Configuration
@EnableAutoConfiguration
class Config {

}

@Autowired
Datastore datastore; (1)
1 A JDBC Datastore type bean is auto-configured ad available from Spring context

Of course, you can use default Spring Boot DataSource auto-configuration features to create the DataSource bean:

spring:
  datasource:
    url: "jdbc:h2:mem:test"
    username: "sa"

holon:
  datastore:
    trace: true

7.1. Multiple JDBC Datastore auto configuration

When the DataSource type beans are auto-configured using the Holon Platform JDBC Module features (see the Holon Platform JDBC Module Spring Boot integration documentation section), the auto-configuration of multiple JDBC Datastores is available out-of-the-box.

The data context id convention is used to provide multiple DataSource and Datastore auto-configuration capabilities: when multiple DataSource type beans are registered, each of them bound to a data context id, the Spring Boot auto-configuration classes will provide to configure a JDBC Datastore bean for each detected DataSource bean, binding the same data context id to the JDBC Datastore bean definitions.

According to the data context id convention, each DataSource and JDBC Datastore pair will be qualified with the corresponding data context id, so that the specific bean instance can be later obtained using the data context id as Spring bean qualifier name.

For example, given an application.yml configuration file as follows:

holon:
  datasource:
    one:
      url: "jdbc:h2:mem:test1"
      username: "sa"
    two:
      url: "jdbc:h2:mem:test2"
      username: "sa"

The auto-configuration feature will configure two DataSource beans:

  • One DataSource bean instance using the one data context id configuration properties, qualified with the one qualifier.

  • Another DataSource bean instance using the two data context id configuration properties, qualified with the two qualifier.

And two corresponding JDBC Datastore beans:

  • One backed by the DataSource bound to the one data context id, qualified with the one qualifier.

  • Another backed by the DataSource bound to the two data context id, qualified with the two qualifier.

So the DataSource and JDBC Datastore beans can be obtained as follows:

// 'one' data context id:
@Autowired @Qualifier("one")
DataSource dataSource1;

@Autowired @Qualifier("one")
Datastore datastore1;

// 'two' data context id:
@Autowired @Qualifier("two")
DataSource dataSource2;

@Autowired @Qualifier("two")
Datastore datastore2;

7.2. Disabling the JDBC Datastore auto-configuration feature

To disable this auto-configuration feature the JdbcDatastoreAutoConfiguration class can be excluded:

@EnableAutoConfiguration(exclude={JdbcDatastoreAutoConfiguration.class})

7.3. Spring Boot starters

The following starter artifacts are available to provide a quick project configuration setup using Maven dependency system:

1. Default JDBC Datastore starter provides the dependencies to the Holon JDBC Datastore Spring Boot integration artifact holon-datastore-jdbc-spring-boot, in addition to:

Maven coordinates:

<groupId>com.holon-platform.jdbc</groupId>
<artifactId>holon-starter-jdbc-datastore</artifactId>
<version>5.1.2</version>

2. JDBC Datastore starter with HikariCP DataSource provides the same dependencies as the default JDBC Datastore starter, adding the HikariCP pooling DataSource dependency.

This way, the HikariCP DataSource will be selected by default by the DataSource auto-configuration strategy if the DataSource type is not explicitly specified using the corresponding configuration property.

See the Holon Platform JDBC Module - Datasource type documentation for details about DataSource types.

Maven coordinates:

<groupId>com.holon-platform.jdbc</groupId>
<artifactId>holon-starter-jdbc-datastore-hikaricp</artifactId>
<version>5.1.2</version>

8. Loggers

By default, the Holon platform uses the SLF4J API for logging. The use of SLF4J is optional: it is enabled when the presence of SLF4J is detected in the classpath. Otherwise, logging will fall back to JUL (java.util.logging).

The logger name for the JDBC Datastore module is com.holonplatform.datastore.jdbc.

9. System requirements

9.1. Java

The Holon Platform JDBC Datastore module requires Java 8 or higher.

9.2. JDBC Drivers

To retrieve back the database generated keys, the JDBC driver in use must be compliant to the JDBC API version 3 or higher.